Dip‐adaptive singular‐value decomposition filtering for seismic reflection enhancement

We present a singular value decomposition (SVD) filtering method for the enhancement of coherent reflections and for attenuation of noise. The method is applied in two steps. First normal move‐out (NMO) correction is applied to shot or CMP records, with the purpose of flattening the reflections. We use a spatial SVD filter with a short sliding window to enhance coherent horizontal events. Then the data are sorted in common‐offset panels and the local dip is estimated for each panel. The next SVD filtering is performed on a small number of traces and a small number of time samples centred around the output sample position. Data in a local window are corrected for linear moveout corresponding to the dips before SVD. At the central time sample position, we sum over the dominant eigenimages of a few traces, corresponding to SVD dip filtering. We illustrate the method using land seismic data from the Tacutu basin, located in the north‐east of Brazil. The results show that the proposed method is effective and is able to reveal reflections masked by ground‐roll and other types of noise.     

Ground-roll attenuation using modified common-offset–common-reflection-surface stacking

We modified the common-offset–common-reflection-surface (COCRS) method to attenuate ground roll, the coherent noise typically generated by a low-velocity, low-frequency, and high-amplitude Rayleigh wave. The COCRS operator is based on hyperbolas, thus it fits events with hyperbolic traveltimes such as reflection events in prestack data. Conversely, ground roll is linear in the common-midpoint (CMP) and common-shot gathers and can be distinguished and attenuated by the COCRS operator. Thus, we search for the dip and curvature of the reflections in the common-shot gathers prior to the common-offset section. Because it is desirable to minimize the damage to the reflection amplitudes, we only stack the multicoverage data in the ground-roll areas. Searching the CS gathers before the CO section is another modification of the conventional COCRS stacking. We tested the proposed method using synthetic and real data sets from western Iran. The results of the ground-roll attenuation with the proposed method were compared with results of the f–k filtering and conventional COCRS stacking after f–k filtering. The results show that the proposed method attenuates the aliased and nonaliased ground roll better than the f–k filtering and conventional CRS stacking. However, the computation time was higher than other common methods such as f–k filtering.     

Seismic attenuation,normal moveout stretch,and low‐frequency shadows underlying bottom simulating reflector events

In many cases, the seismic response of bottom‐simulating reflectors is characterised by low frequencies called “low‐frequency shadow”. Generally, this phenomenon is interpreted as attenuation due to partial saturation with free gas. Actually, this frequency loss may have multiple causes, with a normal moveout stretch as a possible candidate. To analyse this phenomenon, we compute synthetic seismograms by assuming a lossy bottom‐simulating layer, with varying quality factor and thickness, bounded by the upper hydrate‐brine/gas‐brine and lower gas‐brine/brine interfaces. First, we estimate the shift of the centroid frequency of the power spectrum as a function of the travelled distance of the seismic pulse. Then, we perform one‐dimensional numerical experiments to quantify the loss of frequency of the seismic event below the bottom‐simulating reflector as a function of the quality factor of the bottom‐simulating layer and its thickness (due to wave interference). Then, we compute shot gathers to obtain the stacked section, with and without the normal moveout stretch correction and with and without the presence of wave attenuation in the bottom‐simulating layer. The results indicate that the low‐frequency shadow due to the normal moveout stretch is stronger than that due to attenuation and may constitute a false indicator of the presence of gas. In fact, often, the low‐frequency shadow overlies events with higher frequencies, in contradiction with the physics of wave propagation. This is particularly evident when the low‐frequency shadow is so extensive that the presence of high frequencies below cannot be justified by the acquisition geometry.     

方向导数迹变换面波压制

面波是地震勘探中常见的一种相干干扰,它的存在严重的影响着地震记录的信噪比.由于面波和有效波具有相关性且面波的频带和有效波的频带总有重叠的部分,在时域或频域二者不能明显分开,因此在时域或频域采用切除法压制面波会造成子波畸变和有效信息的损失.本文提出一种利用方向导数迹变换压制面波的新方法.文中推导了方向导数迹变换的反变换公式.地震记录的方向导数迹变换(Directional Derivative Trace Transform,DDTT)由两部分组成,一部分主要体现面波,能量集中;另一部分主要体现反射有效波,能量相对分散.根据这两部分能确定压制面波的阈值,通过这一阈值在正变换中压制面波后,再通过反变换返回时-空域就可达到压制面波的目的.理论和实际数据的处理都取得了令人满意的效果,表明了本文提出方法的可行性和有效性.     

LONG PERIOD STATICS DETERMINATION BY INVERSE FILTERING*

The relative time shift of CDP reflections, caused by long period statics, is treated as the result of a filtering process. The shape of the filter is that of a comb having the magnitude and spacing of its teeth determined by the CDP spread geometry. Convolution of a near surface anomaly with a comb filter representing the CDP spread geometry produces the same time fluctuations at CDP reflections (CDP statics) as the stacked traces across the anomaly. Conversely, the near surface time anomaly is given by the convolution of the CDP statics with the inverse of the comb filter. Provided that CDP statics can be separated from noise, dip, and residual normal moveout, it is pcissible to determine long period statics with a relative wavelength of between half a spreadlength and five spreadlengths. The object of this paper is to present the theory and practical applications of the method. Several examples based on synthetic and real data will also be discussed.     

Using the Wiener–Levinson algorithm to suppress ground-roll

In land seismic surveys, the seismic data are mostly contaminated by ground-roll noise, high amplitude and low frequency. Since the ground-roll is coherent with reflections and depends on the source, the spectral band of seismic signal and ground-roll always overlap, which can be clearly seen in the spectral domain. So, separating them in time or frequency domain commonly causes waveform distortions and information missing due to cut-off effects. Therefore, the combination of these factors leads to search for alternative filtering methods or processes. We applied the conventional Wiener–Levinson algorithm to extract ground-roll from the seismic data. Then, subtracting it from the seismic data arithmetically performs the ground-roll suppression. To set up the algorithm, linear or nonlinear sweep signals are used as reference noise trace. The frequencies needed in creating a reference noise trace using analytical sweep signal can be approximately estimated in spectral domain. The application of the proposed method based on redesigning of Wiener–Levinson algorithm differs from the usual frequency filtering techniques since the ground-roll is suppressed without cutting signal spectrum. The method is firstly tested on synthetics and then is applied to a shot data from the field. The result obtained from both synthetics and field data show that the ground-roll suppression in this way causes no waveform distortion and no reduction of frequency bandwidth of the data.     

共转换点道集S变换谱相似性的多波地震数据横波波场提取技术

横波速度动校正后的共转换点(CCP)道集内,同时刻的各道横波信号S变换(ST)谱与其叠加道ST谱具有相似关系.因此,可基于这种相似关系设计自适应滤波器来提取多波地震数据中的横波波场.首先对共中心点(CMP)道集应用纵波速度动校正并在各道减去叠加道来去除数据中的纵波波场;然后在CCP道集应用横波速度动校正,将地震道振幅水平调整至叠加道振幅水平并做S变换,以叠加道ST谱为参考对地震道ST谱进行自适应滤波,去除数据中的残余纵波和噪声;最后,将滤波结果的振幅水平恢复至滤波前振幅水平.理论和实际数据试算表明,本文方法可有效提取多波地震数据中的横波波场,为多波多分量横波数据处理提供新思路.     

Robust adaptive polarization analysis method for eliminating ground roll in 3C land seismics

To improve the data quality of converted waves, and better identify and suppress the strong ground-roll interference in three-component (3C) seismic recordings on land, we present an adaptive polarization filtering method, which can effectively separate the groundroll interference by combining complex polarization and instantaneous polarization analysis. The ground roll noise is characterized by elliptical plane polarization, strong energy, low apparent velocity, and low frequency. After low-pass filtering of the 3C data input within a given time-window of the ground roll, the complex covariance matrix is decomposed using the sliding time window with overlapping data and length that depends on the dominant ground-roll frequency. The ground-roll model is established using the main eigenvectors, and the ground roll is detected and identified using the instantaneous polarization area attributes and average energy constraints of the ground-roll zone. Finally, the ground roll is subtracted. The threshold of the method is stable and easy to select, and offers good groundroll detection. The method is a robust polarization filtering method. Model calculations and actual data indicate that the method can effectively identify and attenuate ground roll while preserving the effective signals.     

转换波四参数速度分析方法在k71地区的应用

3-D converted-wave data were acquired using digital MEMS （micro-electromechanical system） three component （3C） sensors in the alternating sand and shale sequence in the overburden of the Shengli Ken-71 area. This gives rise to serious non-hyperbolic moveout effects in the converted-wave data due to both the asymmetrical ray path and anisotropic effects. Conventional velocity analysis and moveout correction based on isotropic methods do not flatten reflections events. Here, we use a four-parameter theory to evaluate these effects and process the data. These four parameters include the PS converted wave stacking velocity （Vc2）, the vertical velocity ratio （Y0）, the effective velocity ratio （Yeff）, and the anisotropy parameter （xoff）, The method utilizes the moveout information at different offsets to estimate the different parameters and ensures that the events are properly aligned for stacking, As a result, this four-parameter theory leads to an improvement in imaging quality and correlation between the P-waves and converted-waves.     

PLANE-WAVE CONSTRAINTS IN 2D FILTER DESIGN1

A method is presented for developing and/or evaluating 2D filters applied to seismic data. The approach used is to express linear 2D filtering operations in the space-frequency (x–ω) domain. Correction filters are then determined using plane-wave constraints. For example, requiring a vertically propagating plane wave to be unaffected by migration necessitates application of a half-derivative correction in Kirchhoff migration. The same approach allows determination of the region of time-offset space where half-derivative corrections are correct in x–t domain dip moveout. Finally, an x–ω domain dip filter is derived using the constraint that a plane wave be attenuated as its dip increases. This filter has the advantage that it is significantly faster than f–k domain dip filtering and can be used on irregularly spaced data. This latter property also allows the filter to be used for interpolation of irregular data onto a regular grid.     

HORIZONTAL STACKING AND MULTICHANNEL FILTERING APPLIED TO COMMON DEPTH POINT SEISMIC DATA*

The common depth point method of shooting in oil exploration provides a series of seismic traces which yield information about the substrata layers at one location. After normal moveout and static corrections have been applied, the traces are combined by horizontal stacking, or linear multichannel filtering, into a single record in which the primary reflections have been enhanced relative to the multiple reflections and random noise. The criterion used in optimum horizontal stacking is to maximize the signal to noise power ratio, where signal refers to the primary reflection sequence and noise includes the multiple reflections. It is shown when this criterion is equivalent to minimizing the mean square difference between the desired signal (primary reflection sequence) and the weighted horizontally stacked traces. If the seismic traces are combined by multichannel linear filtering, the primary reflection sequence will have undergone some phase and frequency distortion on the resulting record. The signal to noise power ratio then becomes less meaningful a criterion for designing the optimum linear multichannel filter, and the mean square criterion is adopted. In general, however, since more a priori information about the seismic traces is required to design the optimum linear multichannel filter than required for the optimum set of weights of the horizontal stacking process, the former will be an improvement over the latter. It becomes evident that optimum horizontal stacking is a restricted form of linear multichannel filtering.     

HORIZONTAL STACKING AND MULTICHANNEL FILTERING APPLIED TO COMMON DEPTH POINT SEISMIC DATA*

The common depth point method of shooting in oil exploration provides a series of seismic traces which yield information about the substrata layers at one location. After normal moveout and static corrections have been applied, the traces are combined by horizontal stacking, or linear multichannel filtering, into a single record in which the primary reflections have been enhanced relative to the multiple reflections and random noise. The criterion used in optimum horizontal stacking is to maximize the signal to noise power ratio, where signal refers to the primary reflection sequence and noise includes the multiple reflections. It is shown when this criterion is equivalent to minimizing the mean square difference between the desired signal (primary reflection sequence) and the weighted horizontally stacked traces. If the seismic traces are combined by multichannel linear filtering, the primary reflection sequence will have undergone some phase and frequency distortion on the resulting record. The signal to noise power ratio then becomes less meaningful a criterion for designing the optimum linear multichannel filter, and the mean square criterion is adopted. In general, however, since more a priori information about the seismic traces is required to design the optimum linear multichannel filter than required for the optimum set of weights of the horizontal stacking process, the former will be an improvement over the latter. It becomes evident that optimum horizontal stacking is a restricted form of linear multichannel filtering.     

Goos-Hänchen效应对自由表面全反射SV波校正时差的影响

利用SV地震波（偏振化方向在入射面内的横波）在自由表面反射系数的附加相角导出了SV波Goos-Hänchen效应所引起的横向偏移和横向偏移渡越时间,给出了Goos-Hänchen效应正常时差动校正量,讨论了Goos-Hänchen效应对反射SV波正常时差的影响,绘出了横向偏移、Goos-Hänchen效应正常时差及Goos-Hänchen效应正常时差校正量曲线.曲线表明：反射地震波存在负横向偏移效应,在大多数入射角度范围,横向偏移（横向偏移渡越时间）与波长（周期）为同一个数量级.对掠入射波或入射角在临界角附近的入射波,Goos-Hänchen效应对正常时差有较大的测量误差,对反射P、SV波的传播走时产生了不可忽略的影响,因此在实际的地震资料处理中应进行横向偏移效应误差校正.     

OPTIMUM HYPERBOLIC MOVEOUT FILTERS WITH APPLICATIONS TO SEISMIC DATA*

Optimum multichannel filters can be designed to process seismic events falling on hyperbolic moveout curves using the conventional least-squares method. Contrary to the linear moveout filters, autocorrelation and crosscorrelation functions inherent in the normal equations have to be computed numerically. However, computation times of filter coefficients are comparable to linear moveout operators. For a given source-receiver geometry and assuming straight ray-path, relative moveout of a seismic reflection event is dependent on the two way arrival time and rms velocity. Consequently, to avoid overlapping of pass and reject moveout windows, hyperbolic moveout filters have to be designed over time gates rather than for the whole record lengths. Hyperbolic and hyperbolic-linear moveout filters applied to synthetic and field seismic reflection traces show good signal-to-noise (S/N) ratio improvements. Results of some combined synthetic and field data examples are presented.     

基于波形相似特征的微地震事件初至拾取及全局校正

微地震事件初至拾取是井下微地震监测数据处理的关键步骤之一.初至误差的存在会使微地震震源定位结果产生较大偏差,进而影响后续的压裂裂缝解释.通常初至拾取过程对所有的微地震事件选择相同的特征函数并采用一致的拾取参数进行统一处理,然而当事件的能量、震源机制、传播路径以及背景噪声等存在明显差异时,所得初至拾取结果差别显著.为了提高微地震事件初至拾取标准一致性,本文提出基于波形相似特征的初至拾取及全局校正方法.该方法首先利用互相关函数对每个事件内的各道记录进行时差校正,得到初始初至信息并形成叠加道,再对所有事件的叠加道进行全局互相关得到事件间初至相对校正量,最终初至结果可以通过各个事件的初始初至信息与其相对校正量相加得到.方法将所有微地震事件初至结果作为一个整体处理,从而能够克服常规方法初至拾取标准一致性差的缺陷.实际资料处理结果表明,相比于常规方法,该方法可以有效提高事件初至拾取和定位结果的一致性.     

Reflection-constrained 2D and 3D non-hyperbolic moveout analysis using particle swarm optimization

The objective of moveout parameter inversion is to derive sets of parameter models that can be used for moveout correction and stacking at each common midpoint location to increase the signal-to-noise ratio of the data and to provide insights into the kinematic characteristics of the data amongst other things. In this paper, we introduce a data-driven user-constrained optimization scheme that utilizes manual picks at a point on each reflector within a common midpoint gather to constrain the search space in which an optimization procedure can search for the optimal parameter sets at each reflection. The picks are used to create boundary curves which can be derived approximately via an optimization technique or analytically via the derivation of an analytical bounds function. In this paper, we derive analytical forms of bounds functions for four different moveout cases. These are normal moveout, non-hyperbolic moveout, azimuthally dependent normal moveout and azimuthally dependent non-hyperbolic moveout. The optimization procedure utilized here to search for the optimal moveout parameters is the particle swarm optimization technique. However, any metaheuristic optimization procedure could be modified to account for the constraints introduced in this paper. The technique is tested on two-layer synthetic models based on three of the four moveout cases discussed in this paper. It is also applied to an elastic forward modelled synthetic model called the HESS model, and finally to real 2D land data from Alaska. The resultant stacks show a marked improvement in the signal-to-noise ratio compared to the raw stacks. The results for the normal moveout, non-hyperbolic moveout and azimuthally dependent normal moveout tests suggest that the method is viable for said models. Results demonstrate that our method offers potential as an alternative to conventional parameter picking and inversion schemes, particularly for some cases where the number of parameters in the moveout approximation is 2 or greater.     

EFFICIENT MULTICHANNEL FILTERING OF SEISMIC DATA1

Multichannel filters are used to eliminate coherent noise from surface seismic data, for wavefield separation from VSP stacks, and for signal enhancement. Their success generally depends on the choice of the filter parameters and the domain of application. Multichannel filters can be applied to shots (monitors), common-receiver traces, CDP traces and stacked sections. Cascaded applications in these domains are currently performed in the seismic industry for better noise suppression and for signal enhancement. One-step shot-domain filtering is adequate for some applications. However, in practice, cascaded applications in shot-and common-receiver domains usually give better results when the S/N ratio is low. Multichannel filtering after stacking (especially after repeated applications in shot and/or receiver domains) may create undesirable results such as artificial continuations, or smearing and smoothing of small features such as small throw faults and fine stratigraphic details. Consequently, multichannel filtering after stacking must be undertaken with the utmost care and occasionally only as a last resort. Multichannel filters with fan-shaped responses (linear moveout filters) should be applied after NMO correction. These are the filters commonly used in the seismic industry where they have such names as velocity filters, moveout filters, f-k filters and coherency filters. Filtering before NMO correction may result in break-up and flattening especially of those shallow reflection events with relatively higher curvatures and diffractions. NMO correction is needed prior to wavefield separation from VSP stacks for the same practical reasons outlined above whenever source-receiver offsets are involved. Creation of artificial lineup and smearing at the outputs of multichannel filters is presently the common practical concern. Optimum multichannel filters with well-defined pass, reject and transition bands overcome the latter problems when applied before stacking and after NMO correction. The trace dimension of these filters must be kept small to avoid such lineups and the smoothing of small structures. Good results can be obtained with only five traces, but seven traces seems to be a better compromise both in surface and well seismic applications. The so-called f-k filtering and τ-p domain filtering are no exceptions to the above practical considerations. Residual static computations after multichannel filtering also need special consideration. Since multichannel filtering improves spatial continuity, residual static algorithms using local correlation, i.e. nonsurface-consistent algorithms, may be impractical especially after multichannel filtering.     

VTI介质长偏移距非双曲动校正公式优化

常规Alkhalifah动校正公式精度低,不能精确描述各向异性介质长偏移距地震反射同相轴的时距关系.本文以提高VTI介质长偏移距地震资料动校正公式的精度为目标,在分析VTI介质常规动校正方程的基础上,根据误差最小原理建立优化校正系数图版,实现对常规动校正公式大偏移距误差的修正,建立最优化校正Alkhalifah动校正方程,实现了对VTI介质长偏移距地震资料常规动校正方程的改进.之后由Fomel群速度公式导出高精度VTI模型长偏移距时距函数,提出了高精度VTI介质长偏移距地震资料动校正方程.将以上的动校正方程用于各向异性参数反演,模型计算表明最优化校正Alkhalifah动校正方程的反演精度是常规长偏移距动校正方程反演精度的2～4倍,高精度动校正方程的反演精度是常规动校正方程反演精度的2～8倍.     

噪声水平上的爆炸余震信号提取

文中采用窄带滤波、傅里叶反变换及小波分析在噪声水平上提取弱余震信号。窄带滤波能够在背景噪声水平上以及（－10）－（20）dB记录中提取有用信息，但是往往产生截断误差，如果数字序列具有较大的初始幅值，所提取的波形在截断处发生畸变。傅氏反变换从负信噪比的记录中提取的信号质量较差，伴有高频干扰成分，对于信噪比为正数的记录，傅氏反变换提取的波形是良好的，该种方法同滤波方法一样，也存在截断误差。小波分析从信噪比为负数的记录中提取的信号不理想，而从信噪比为正数的记录中提取的信号质量最好，波形完整，首尾清晰，基线平直，无截断误差。窄带滤波，傅氏反变换及小波分析有两个共同点，基一，都能够从强背景噪声中提取有用信息；其二，信噪比越大，获取的信号质量越高。     

STACKING FILTERS AND THEIR CHARACTERIZATION IN THE (f—k) DOMAIN *

The implementation of a stacking filter involves the filtering of each trace with an individual filter and the subsequent summing of all outputs. The actual position of a trace in space as well as certain simultaneous shifts of traces and filter components in time do not influence the process. The resulting output is consequently invariant to various arbitrary coordinate transformations. For a certain useful class of ensembles of non-linear moveout arrival times for signals a particular transformation can be found which transforms a given ensemble into one consisting only of straight lines. It is thus possible to reduce, for instance, the analysis of a stacking filter designed for hyperbola-like moveout curves to the analysis of a velocity filter with linear moveout curves. As the (f—k) transform is a very useful concept to describe a velocity filter, it can consequently be applied to characterize a stacking filter in regard to its performance on input signals with non-linear moveout.